holylovenia
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Upload indspeech_newstra_ethnicsr.py with huggingface_hub
Browse files- indspeech_newstra_ethnicsr.py +12 -12
indspeech_newstra_ethnicsr.py
CHANGED
@@ -21,9 +21,9 @@ from typing import Dict, List, Tuple
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import datasets
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from
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from
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from
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_CITATION = """\
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@inproceedings{sakti-cocosda-2013,
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@@ -84,17 +84,17 @@ _URLS = {
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_SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]
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_SOURCE_VERSION = "1.0.0"
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-
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def
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if lang == "":
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raise ValueError(f"Invalid lang {lang}")
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if schema != "source" and schema != "
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raise ValueError(f"Invalid schema: {schema}")
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return
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name="indspeech_newstra_ethnicsr_{overlap}_{lang}_{schema}".format(lang=lang, schema=schema, overlap=overlap),
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version=datasets.Version(version),
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description="indspeech_newstra_ethnicsr {schema} schema for {lang} language with {overlap}ping dataset".format(lang=_lst_LANG[_lst_STD_LANG[lang]], schema=schema, overlap=overlap),
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@@ -110,10 +110,10 @@ class INDspeechNEWSTRAEthnicSR(datasets.GeneratorBasedBuilder):
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The 'overlap' keyword in the dataset-name combines both sub-datasets, while 'nooverlap' will only use dataset 1
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"""
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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BUILDER_CONFIGS = [
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[
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DEFAULT_CONFIG_NAME = "indspeech_newstra_ethnicsr_jav_source"
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@@ -129,7 +129,7 @@ class INDspeechNEWSTRAEthnicSR(datasets.GeneratorBasedBuilder):
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"gender": datasets.Value("string"),
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}
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)
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elif self.config.schema == "
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features = schemas.speech_text_features
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return datasets.DatasetInfo(
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@@ -204,7 +204,7 @@ class INDspeechNEWSTRAEthnicSR(datasets.GeneratorBasedBuilder):
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}
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yield id, ex
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elif self.config.schema == "
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ex = {
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"id": str(id),
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"speaker_id": str(Path(row).parent).split("/")[1],
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import datasets
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from seacrowd.utils import schemas
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from seacrowd.utils.configs import SEACrowdConfig
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from seacrowd.utils.constants import Tasks
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_CITATION = """\
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@inproceedings{sakti-cocosda-2013,
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_SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]
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_SOURCE_VERSION = "1.0.0"
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_SEACROWD_VERSION = "2024.06.20"
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def seacrowd_config_constructor(lang, schema, version, overlap):
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if lang == "":
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raise ValueError(f"Invalid lang {lang}")
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if schema != "source" and schema != "seacrowd_sptext":
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raise ValueError(f"Invalid schema: {schema}")
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return SEACrowdConfig(
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name="indspeech_newstra_ethnicsr_{overlap}_{lang}_{schema}".format(lang=lang, schema=schema, overlap=overlap),
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version=datasets.Version(version),
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description="indspeech_newstra_ethnicsr {schema} schema for {lang} language with {overlap}ping dataset".format(lang=_lst_LANG[_lst_STD_LANG[lang]], schema=schema, overlap=overlap),
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The 'overlap' keyword in the dataset-name combines both sub-datasets, while 'nooverlap' will only use dataset 1
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"""
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
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BUILDER_CONFIGS = [seacrowd_config_constructor(lang, "source", _SOURCE_VERSION, overlap) for lang in _lst_STD_LANG for overlap in ["overlap","nooverlap"]] +\
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[seacrowd_config_constructor(lang, "seacrowd_sptext", _SEACROWD_VERSION, overlap) for lang in _lst_STD_LANG for overlap in ["overlap","nooverlap"]]
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DEFAULT_CONFIG_NAME = "indspeech_newstra_ethnicsr_jav_source"
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"gender": datasets.Value("string"),
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}
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)
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elif self.config.schema == "seacrowd_sptext":
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features = schemas.speech_text_features
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return datasets.DatasetInfo(
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}
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yield id, ex
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elif self.config.schema == "seacrowd_sptext":
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ex = {
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"id": str(id),
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"speaker_id": str(Path(row).parent).split("/")[1],
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